Graph clustering
if(!file.exists("../analysis/filtered_EPI_int_clus.rds")){
alldata = readRDS(file = "../analysis/filtered_EPI_int.rds")
alldata@active.assay = "CCA"
alldata <- FindNeighbors(alldata, dims = 1:30, k.param = 350, prune.SNN = 1/15)
names(alldata@graphs)
pheatmap(alldata@graphs$CCA_nn[1:200, 1:200], col = c("white", "black"), border_color = "grey90",
legend = F, cluster_rows = F, cluster_cols = F, fontsize = 2)
# Clustering with louvain (algorithm 1)
for (res in c(0.1, 0.25, 0.5, 1, 1.5, 2)) {
alldata <- FindClusters(alldata, graph.name = "CCA_snn",
resolution = res, algorithm = 1)
}
saveRDS(alldata, file = "../analysis/filtered_EPI_int_clus.rds")
}else{
alldata = readRDS(file = "../analysis/filtered_EPI_int_clus.rds")
}
plot_grid(ncol = 2,
DimPlot(alldata, reduction = "umap", group.by = "CCA_snn_res.0.5",
label = TRUE) + NoLegend() +
ggtitle("louvain_0.5") + theme(legend.position = "bottom"),
DimPlot(alldata, reduction = "umap", group.by = "CCA_snn_res.1",
label = TRUE) + NoLegend() +
ggtitle("louvain_1") + theme(legend.position = "bottom"),
DimPlot(alldata, reduction = "umap", group.by = "CCA_snn_res.1.5",
label = TRUE) + NoLegend() +
ggtitle("louvain_1.5") + theme(legend.position = "bottom"),
DimPlot(alldata, reduction = "umap", group.by = "CCA_snn_res.2",
label = TRUE) + NoLegend() +
ggtitle("louvain_2") + theme(legend.position = "bottom"))

clustree(alldata@meta.data, prefix = "CCA_snn_res.")

QC, CCA louvain 0.5
table(alldata$CCA_snn_res.0.5)
VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.0.5" ,
ncol = 3, pt.size = 0.1)

VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.0.5" ,
ncol = 3, pt.size = 0)

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=CCA_snn_res.0.5, fill=orig.ident)) + geom_bar(position = "fill")

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=orig.ident, fill=CCA_snn_res.0.5)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(x=Type, fill=CCA_snn_res.0.5)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(fill=Type, x=CCA_snn_res.0.5)) + geom_bar(position = "fill")

DotPlot(alldata, features = c("Ptprc","Epcam"), group.by = "CCA_snn_res.0.5",
assay = "CCA") + coord_flip()

##
## 0 1 2 3 4
## 2283 2209 1249 1164 1107
QC, CCA louvain 1
table(alldata$CCA_snn_res.1)
VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.1" ,
ncol = 3, pt.size = 0.1)

VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.1" ,
ncol = 3, pt.size = 0)

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=CCA_snn_res.1, fill=orig.ident)) + geom_bar(position = "fill")

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=orig.ident, fill=CCA_snn_res.1)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(x=Type, fill=CCA_snn_res.1)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(fill=Type, x=CCA_snn_res.1)) + geom_bar(position = "fill")

DotPlot(alldata, features = c("Ptprc","Epcam"), group.by = "CCA_snn_res.1",
assay = "CCA") + coord_flip()

##
## 0 1 2 3 4 5 6 7
## 1644 1254 1244 1167 953 727 633 390
QC, CCA louvain 1.5
table(alldata$CCA_snn_res.1.5)
VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.1.5" ,
ncol = 3, pt.size = 0.1)

VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.1.5" ,
ncol = 3, pt.size = 0)

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=CCA_snn_res.1.5, fill=orig.ident)) + geom_bar(position = "fill")

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=orig.ident, fill=CCA_snn_res.1.5)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(x=Type, fill=CCA_snn_res.1.5)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(fill=Type, x=CCA_snn_res.1.5)) + geom_bar(position = "fill")

DotPlot(alldata, features = c("Ptprc","Epcam"), group.by = "CCA_snn_res.1.5",
assay = "CCA") + coord_flip()

##
## 0 1 2 3 4 5 6 7
## 1517 1232 1214 1172 988 754 741 394
QC, CCA louvain 2
table(alldata$CCA_snn_res.2)
VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.2" ,
ncol = 3, pt.size = 0.1)

VlnPlot(alldata, features = c("nFeature_CCA", "nCount_CCA", "percent_mito", "percent_ribo",
"S.Score", "G2M.Score"), group.by = "CCA_snn_res.2" ,
ncol = 3, pt.size = 0)

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=CCA_snn_res.2, fill=orig.ident)) + geom_bar(position = "fill")

#plot as proportion or percentage of cluster
ggplot(alldata@meta.data, aes(x=orig.ident, fill=CCA_snn_res.2)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(x=Type, fill=CCA_snn_res.2)) + geom_bar(position = "fill")

ggplot(alldata@meta.data, aes(fill=Type, x=CCA_snn_res.2)) + geom_bar(position = "fill")

DotPlot(alldata, features = c("Ptprc","Epcam"), group.by = "CCA_snn_res.2",
assay = "CCA") + coord_flip()

##
## 0 1 2 3 4 5 6 7 8
## 1219 1187 1179 1013 916 829 738 537 394